GPT-5.4-Cyber vs Qwen3.5-4B
GPT-5.4-Cyber (2026) and Qwen3.5-4B (2026) are frontier reasoning models from OpenAI and Alibaba. GPT-5.4-Cyber ships a not-yet-sourced context window, while Qwen3.5-4B ships a 262K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
GPT-5.4-Cyber is safer overall; choose Qwen3.5-4B when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | GPT-5.4-Cyber | Qwen3.5-4B |
|---|---|---|
| Decision fit | Vision | Long context and Vision |
| Context window | — | 262K |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.4-Cyber uniquely exposes Reasoning in local model data.
- Local decision data tags GPT-5.4-Cyber for Vision.
- Qwen3.5-4B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-4B uniquely exposes Vision in local model data.
- Local decision data tags Qwen3.5-4B for Long context and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GPT-5.4-Cyber
Unavailable
No complete token price in local provider data
Qwen3.5-4B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.4-Cyber and Qwen3.5-4B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- Qwen3.5-4B adds Vision in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-4B and GPT-5.4-Cyber; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision before moving production traffic.
- GPT-5.4-Cyber adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-14 | 2026-03-02 |
| Context window | — | 262K |
| Parameters | — | 4B |
| Architecture | decoder only | - |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.4-Cyber | Qwen3.5-4B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | GPT-5.4-Cyber | Qwen3.5-4B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Qwen3.5-4B and reasoning mode: GPT-5.4-Cyber. Both models share multimodal input, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: GPT-5.4-Cyber has no token price sourced yet and Qwen3.5-4B has no token price sourced yet. Provider availability is 0 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-5.4-Cyber when reasoning depth are central to the workload. Choose Qwen3.5-4B when vision-heavy evaluation are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Is GPT-5.4-Cyber or Qwen3.5-4B open source?
GPT-5.4-Cyber is listed under Proprietary. Qwen3.5-4B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.4-Cyber or Qwen3.5-4B?
Qwen3.5-4B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.4-Cyber or Qwen3.5-4B?
Both GPT-5.4-Cyber and Qwen3.5-4B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, GPT-5.4-Cyber or Qwen3.5-4B?
GPT-5.4-Cyber has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
When should I pick GPT-5.4-Cyber over Qwen3.5-4B?
GPT-5.4-Cyber is safer overall; choose Qwen3.5-4B when vision-heavy evaluation matters. If your workload also depends on reasoning depth, start with GPT-5.4-Cyber; if it depends on vision-heavy evaluation, run the same evaluation with Qwen3.5-4B.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.